Perceived Utilities of COVID-19 Related Chatbots in Saudi Arabia: a Cross-sectional Study Acta Informatica Medica

Further, it reduces peak load for service providers, increases program enrollments, automates frequently asked questions (FAQs), and keeps customers engaged by simplifying home energy management. Staying ahead of the technology curve means strengthening your competitive advantage. That is why we give you data-driven innovation insights into the utility sector. This time, you get to discover 5 hand-picked startups building chatbots for utility companies.

But yes, the utility of human agents will forever be there for complex situations. To our knowledge, this is the first study exploring Saudi Arabia’s acceptability of health chatbots related to COVID-19 from the perspective of the end-users. In addition, our findings indicated that the participants were more willing to use health chatbot to seek general information about COVID-19 over seeking information about COVID-19 medical treatments. Fourthly, chatbots can track COVID-19 symptoms (e. g, fever, headache, shortness of breath) and various health aspects (e. g, physical activities, heart rate, diet) on a daily basis with ongoing symptom measurements. The users’ collected data allows the bots to categorise them into groups based on the severity of their symptoms, and–using machine learning–predict the cases who are at higher risk. Customised health advice and recommendations about self-care are then provided to the user based on the recorded symptoms.

Advantages of chatbots in customer service

Help With Relocating— As customers move out, they need to fill out several forms to declare they are logging out of one place and logging into another. Via chatbots, without any complicated process, they can simply carry out the handover process through chatbots. Chatbots can ask for certain information necessary for the relocation, like the old meter readings, the handover dates, customer information, etc. After collecting the data, it can then notify the competent bodies of the alterations. Conversational AI chatbots become your automated sales and service solution. JennyBot answers FAQs at lightspeed so your customer service advisors can focus on complex questions without burning out on simpler and frequent queries.

• The questionnaire was built in Microsoft Form and comprised two sections and 20 questions.
• Experience in heavily regulated industries such as healthcare helps keep the APIs scheduling and configuring robots difficult to breach.
• The virtual assistant will listen to you, respond, and perform tasks such as sending a mail, conducting searches, opening apps, providing weather information, and so on.
• With WhatsApp chatbots, you can scale up your customer support without having to add more manpower.
• Big Data are opening up new possibilities and efficiencies that plays a major role on economics.
• Startups such as the examples highlighted in this report focus on chatbots, advanced analytics, digital maintenance as well as predictive analytics.

These are ready-made conversation scenarios that cover all most common questions Energy companies receive. For a chatbot-only approach, a simple snippet is pasted into your website. Your GetJenny Customer Success Manager will always be on hand to help you. The old rules of the application development lifecycle, which required lengthy software packaging, manual testing, environment creation, and software deployment are falling away, Menendez says. “By leveraging the cloud and automation, we can shorten this lifecycle significantly and deliver more to our customers faster,” he says. The users of the utilities sector often review the energy usage once the bill for utilities is already generated.

REVE Chat Blog

They route customers to the right sales or support agent and provide a personalized experience. The “better together” approach to chatbots and live chat automates repetitive task (like FAQs) and supports agents – working together, they deliver top notch customer care. “I don’t want to call up the utility, they take away a lot of time from my day,” said an annoyed utility customer. Due to large call volumes, utility customer care lacks the efficiency of answering customer queries in a brief time. For years, the utilities have struggled to bring down their response time. Finding solutions to answer customer queries instantly, came the chatbots.

Large language models like ChatGPT proved that intelligent chatbots and conversational AI aren’t just nice ideas, they’re real and an important part of modern businesses. Others speaking at the event were more cynical about the benefits of chatbots. Nicola Millard, customer insights and futurology at BT Global Services, said she believes that despite the “hype” around chatbots, they are currently only useful for “basic” tasks and are only as good as a company’s data. It claims it was the first within the home utilities sector to launch a chatbot to deal with customer queries.

Automating Energy and Utility Businesses With RPA

Nearly 55% of online shoppers terminate a purchase as they can’t find needed answers to their questions quickly enough. Thus, the massive advantage of a chatbot for business is an ability to help clients at any time. Even modest improvements in customer experience result in higher customer loyalty. In particular, the probability of recommending a company and the intention to make future purchases can be significantly influenced by even small improvements in customer experience. Our security and privacy policies are trusted by government bodies, healthcare providers and financial institutions.

After securing the approval of Jazan University’s Human Research Ethics Committee to conduct a quantitative descriptive study, we designed and implemented an online survey. The first page of the survey included the plain language statement and the participant consent form. Participants were also informed that they could withdraw from the survey without repercussion before submitting the form. At Master of Code, we specialize in helping businesses leverage Generative AI to drive impactful, engaging experiences for your customers.

Insights for All-Stars

Since utilities are service-oriented businesses, customer communication is an integral part of their services. Although the utility sector receives a large number of queries and complaints on an everyday basis, providing 24/7 support is an uphill task. Chatbots, on the other hand, solve this problem by automating the most common replies using artificial intelligence (AI). Chatbots interpret user questions using natural language processing (NLP) and provide an instant pre-set answer.

On the contrary, a lot of customers still prefer human interactions over machines for various reasons. A voice bot is a voice-to-text and text-to-speech communication channel powered by AI and natural language understanding (NLU). AI technology aids in identifying key speech signals and determining the optimal conversational response. The text-to-speech (TTS) engine subsequently completes the interaction by converting the message into audio or voice.

The future of customer experience is conversational.

This is an effective workaround when the bot cannot detect keywords in the typed input. Live chat is a type of chat system that sits on the webpage or in your mobile application and works as a consumer’s window to your support team and contact center. Using this mechanism, chatbots incorporate routing capabilities to assign discussions in real-time. With AI-driven decision-making mechanisms, a chatbot can be extremely effective, provided they have a thorough understanding of your organization, its customers, and its context. This functionality is primarily used by large enterprises like e-commerce as well as other high-volume businesses that demand scale. Aisera’s Conversational AI solution empowers customers with an unprecedented level of self-service accompanied by an Alexa-like natural language interface.

• A chatbot can simulate a human being to interact with the people in real-time, using the natural language and sends its response from a knowledge base and a set of business rules.
• In this video, we’ll walk through several different ways a chatbot can help utility customers answer important questions, manage their account, and eliminate hold or wait times.
• With the utilities chatbot on WhatsApp, customers can simply type in their queries and get instant responses to their issues.
• Due to advanced process flows achieved with the help of technologies like machine learning and natural language processing, chatbots have the ability to monitor systems and meet customer expectations.
• Chatbots can work at any second of any day and can reply to a limitless number of customers in an instant.
• We have used the examples of some popular utilities to explain them specifically.

On the other hand, chatbots enable companies to interact with a virtually endless number of clients in a personalized way, to be scaled up or down based on current requirements. One can provide an almost “humanlike” service tailored to each individual, even as the chatbot is deployed to millions of customers at the same time. The rise of chatbots in recent years is rooted in the accelerating pace of digital transformation. Businesses are increasingly migrating from traditional modes of communication to digital channels to interact and transact with their customers. Businesses use artificial intelligence (AI) to unlock new efficiencies in various customer-facing functions, and chatbots are among the top applications of AI in an enterprise.

Analysis of the user’s request

By integrating ChatGPT into their systems, businesses can provide personalized and interactive experiences to their customers. It can assist in handling inquiries, providing recommendations, or even generating creative content. Enterprises can utilize the power of ChatGPT to enhance their communication, metadialog.com streamline their business processes, and improve overall customer satisfaction. However, In more complex & deep learning-based chatbots, the response generation process could be more nuanced, considering context from language models’ past interactions and using more complex means to generate responses.